Don't know what Strava is? I'm tempted to say you've been living under a rock! Depending on who you talk to, Strava is either the best or the worst thing to happen to cycling in a long time...
Essentially, Strava is simply a recording tool for your rides. You use a GPS (via either your smartphone or bike computer) which records your ride, and then you upload it later to Strava. Simple so far, right?
What Strava is most famous for is its KOM (or QOM for the ladies) leaderboards. Segments are created (a segment is just a stretch of road - doesn't have to be uphill - and can be any length, long or short) by users, and then a leaderboard is created that ranks you on an all-time list for that particular stretch of road.
These KOM leaderboards have polarised the cycling community in many ways. Some see it as just a fun way to test yourself, others see it as wrecking the usual convivial nature of group rides and turning everything into a race. Personally, I think its just a bit of fun - but that's not why I'm talking about Strava in this post.
The real value of Strava is in training analysis. Keep in mind I'm talking about the free version here - there is also a premium 'paid' version that lets you record and analyse power and heartrate as well.
Keeping you honest
If you asked me 6 months ago how often I trained, I'd say "Oh, roughly 7-8 hours a week". Looking back at Strava, I know now that on my biggest months, I averaged just under 6 hours a week! Even my best weeks were no higher than 7 hours (with just the one outlier - a 9 hour week).
Knowing what I do (and don't do!), has helped me to develop some realistic training goals for the next month and year ahead.
Strava shows weekly volume graphs (in either mileage or hours), which allows you to match up how you are feeling and performing with how you have been training, and thus start to look at how best to improve.
As an example, I've been able to see where I've felt in the best form and other periods where I've felt sluggish, and consider my training loads around those times to identify some correlations.
One of the more recent additions to Strava has been 'speed graphs'. Basically, for each ride (or segment) it will show a graph of your speed from start to finish.
This aspect is very useful for racing. I've been able to look at some criteriums I've done, seen how the speed has changed over the course of the race in an easy-to-view line graph, and matched that up to when I've felt flat or struggling.
Similarly it has helped with my longer interval training. I can see how my speed has waivered (or not) for some intervals and gotten to understood where I've backed off and could've pushed harder, or conversely been pleased when I've seen how I've managed to hold my pace high throughout each interval.
Not a magic bullet
Don't get me wrong - I know I am talking Strava up here, and I feel I've gotten a lot out of it now that I've racked up about 6 months worth of data into it. But I should point out that simply recording data into the application won't change anything (unless you get pleasure from staring at pretty graphs). The value is having the data there to analyse, and that analysis is facilitated by having a variety of easily accessible formats (eg graphs, calendars) in which to view it.
So should you use Strava?
If you've never used Strava, or simply written it off as a way for ego-driven speedsters to show off their best times, then I'd urge you to look more closely at how Strava can work for you - it really is so much more than just a 'leaderboard'.
It's ease of use (Android or iOS app on your smartphone), simple user interface on your PC, and super-low cost (free!) mean there are no real barriers to entry. Personally, I use my Android smartphone to record my rides - I just initialise the GPS function before I set off, throw it in my back jersey pocket, and away I go. I then upload the ride data at home using my own wifi, so I don't need to use mobile data at any stage at all!
Allow yourself to gather a few months worth of data to give yourself a good basis for training analysis, and then go from there. If it turns out not to be your thing - then so be it. But if you have an interest in developing your training off the back of real data, then you should give this application a try.